Examples of using Stochastic processes in English and their translations into Romanian
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Probabilty and Stochastic Processes;
Stochastic processes: definitions and classification.
Interdependence or relationship between two stochastic processes.
Stochastic processes arising in the theory of particle counters".
He is best known for his work on theory of stochastic processes.
Stochastic processes of relaxation and fluctuations in cluster-based media.
Knowledge of Statistical Physics and/or stochastic processes would be advantageous.
The Master in Financial Mathematics, jointly organized by ISCTE Business School and the Department of Mathematics of the Faculty of Sciences of the University of Lisbon,aims at the advanced training of staff in the area of stochastic processes applied to Finance.
In the 1930s and 1940s, rigorous mathematical foundations for stochastic processes were developedBühlmann 1997, p.
To give to the students the basic notions of the stochastic processes which are necessary in the model process of the economic, social and other phenomena.
For those who are interested, the program offers courses in quantitative finance,probability, stochastic processes, and statistics.
The program is based on a mathematical background,which involves probability theory, stochastic processes, mathematical and computational statistics, optimization, econometrics, operational research, financial and insurance mathematics.
An institution may calibrate its EPE model using either historic market data ormarket implied data to establish parameters of the underlying stochastic processes, such as drift, volatility and correlation.
The program provides methodologies of advanced mathematical calculus, in particular,probability and stochastic processes and linear systems in order to introduce the necessary tools to model and formalize the solutions of complex electronics engineering problems focusing on telecommunications.
These current methods are based on differential ecuations(ODE) or stochastic processes(Gillespie algorithm).
In algebraic topology, the study of homotopy theory is essentially that of discrete invariants of function spaces;In the theory of stochastic processes, the basic technical problem is how to construct a probability measure on a function space of paths of the process(functions of time); In category theory the function space is called an exponential object or map object.
In 1957 he received the Academic Doctor's Degree in Mathematics for his thesis entitled"Stochastic processes arising in the theory of particle counters"(1957).
Specific subjects in the different subprograms: Mathematics of Engineering: Numerical analysis, solutions of differential equations Linear models andapplications Numerical mathematics Stochastic processes Mathematics of Finance: Statistics Stochastic systems Financial science Mathematics of Computer Science: Data mining Mathematical theory of networks Theory of complexity Design, analyzing and implementation of algorithms and data structures Cryptography and data security Information theory Codes and symmetric structures…[-].
The goal of the present research grant is the study of some related problems based on fundamental mathematical research in the area of stochastic processes, complex analysis and potential theory, the key point being the Brownian motion.
Functional and Harmonic Analysis methods in Matriceal Analysis, generalized stochastic processes and in the study of some classes of operators.
Nucleation is usually a stochastic process, so even in two identical systems nucleation will occur at different times.[1][2][3] This behaviour is similar to radioactive decay.
It is subject to a stochastic process and can be described qualitatively and quantitatively; it is not directly measurable.
He was responsible for numerous research projects dealing with groundwater hydraulic,tracer tests, transport of pollutants, investigation of contaminated sites and stochastic modeling processes of reactive and non-reactive transport in groundwater.
This research project is concerned with studying a class of stochastic dynamic decision models that comprises stochastic versions of classical discrete optimal control problems, discrete Markov decision processes and stochastic positional games with average and discounted payoffs.